Extended thermal rating calculations of 400 kV XLPE cables for urban grid applications based on long-term experimental data

Abstract

Conventional rating calculations for power cables are based on the analytical methods given by IEC standards. These methods lead to rather conservative results though, which has been acceptable in the past since high-voltage cables are normally not loaded to their thermal limits and are rather operated in cold conditions, relatively speaking. However, the power system is undergoing a transition towards increasing and more dynamic loads and, therefore, towards the need for a more flexible and resilient grid. This applies in particular to cable systems in urban areas where high-voltage cables are used due to the infeasibility of overhead lines and where the renewal or expansion of those systems is attached to high installation costs. An optimized use of existing and future cable systems is a crucial feature in order to cope with the increasing requirements. Therefore, an attempt is made to combine the advantages of the different calculation methods in order to improve performance and efficiency. Furthermore, there is high potential to improve cable calculations with the application of artificial intelligence (AI). First, however, these procedures must be brought together to be evaluated, and experience in the application of AI in cable calculations must be gathered. Therefore, an actual 400 kV cable system with a typical urban laying profile was set up in a cooperation project between Vienna’s grid operator Wiener Netze GmbH and the High Voltage Test Laboratory Graz Ltd. to develop and validate calculation methods. In addition, it is investigated which input parameters are necessary, what effect do they have on the result and which accuracy and efficiency can be achieved.

This is a preview of subscription content, log in to check access.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.

References

  1. 1.

    IEC 60287:2020 SER (Series), Electric cables – Calculation of the Current Rating.

  2. 2.

    IEC 60853-1:1985, Calculation of the cyclic and emergency current rating of cables. Part 1: Cyclic rating factor for cables up to and including 18/30(36) kV.

  3. 3.

    IEC 60853-2:1989, Calculation of the cyclic and emergency current rating of cables. Part 2: Cyclic rating of cables greater than 18/30(36) kV and emergency ratings for cables of all voltages.

  4. 4.

    IEC 60853-3:2002, Calculation of the cyclic and emergency current rating of cables. Part 3: Cyclic rating factor for cables of all voltages, with partial drying of the soil.

  5. 5.

    Nahman, J., et al. (2001): Determination of the current carrying capacity of cables using the finite element method. Electr. Power Syst. Res., 61, 109–117.

    Article  Google Scholar 

  6. 6.

    Aras, F., et al. (2005): An assessment of the methods for calculating ampacity of underground power cables. Electr. Power Compon. Syst., 33(11), 1385–1402.

    Article  Google Scholar 

  7. 7.

    Pilgrim, J., et al.(2013): Current rating optimisation for offshore wind farm export cables. In EWEA offshore, Frankfurt, November 2013.

    Google Scholar 

  8. 8.

    IEC TR 62095:2003, Electric cables – calculation for current ratings – finite element method.

  9. 9.

    CIGRE Working Group B1.56: Overview of CIGRE WG B1.56 regarding the verification of cable current ratings. Report C6-6. In Jicable 2019 – 10th International Conference on Insulated Power Cables, Versailles, July 2019.

  10. 10.

    Working Group WG B1.45: Thermal monitoring of cable circuits and grid operators’ use of dynamic rating systems. CIGRE TB 756, February 2019.

  11. 11.

    Deutsche Bundesregierung: Strategie Künstliche Intelligenz der Bundesregierung, Berlin, November 2018.

  12. 12.

    Begleitforschung Smart Service Welt II, Institut für Innovation und Technik (iit) in der VDI/VDE Innovation + Technik GmbH, Anwendung künstlicher Intelligenz im Energiesektor, dena, Berlin, May 2019.

  13. 13.

    German Energy Agency: Artificial intelligence for the integrated energy transition, dena, Berlin, September 2019.

  14. 14.

    Ramos, C., et al. (2011): AI in power systems and energy markets. IEEE Intell. Syst., 26(2), 5–8.

    Article  Google Scholar 

  15. 15.

    Venkata, S. S., et al. (1993): Applying AI systems in the T&D arena. IEEE Comput. Applic. Power.

  16. 16.

    Liu, C. (1997): Intelligent system applications to power systems. IEEE Comput. Applic. Power.

  17. 17.

    Dahhaghchi, I., et al. (1997): AI application areas in power systems. IEEE Expert, 12(1), 58–66.

    Article  Google Scholar 

  18. 18.

    Dubitsky, S., et al.(2016): Comparison of finite element analysis to IEC-60287 for predicting underground cable ampacity. In IEEE international energy conference, Energycon, Leuven, April 2016.

    Google Scholar 

  19. 19.

    Ainhirn, F., et al. (2019): Extended approach for calculating thermal stress and ampacity of high voltage cable systems based on experimental data. In Jicable 2019 – 10th international conference on insulated power cables, Versailles, July 2019. Report C6-3

    Google Scholar 

  20. 20.

    Likos, W. (2014): Modeling thermal conductivity dryout curves from soil-water characteristic curves. J. Geotech. Geoenviron. Eng., 140(5), 04013056.

    Article  Google Scholar 

  21. 21.

    Ainhirn, F., et al.(2020): A cyclic simulation approach for transient thermal rating calculations of underground power cables. In CIGRE SEERC 2020, Vienna, June 2020.

    Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to F. Ainhirn.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Paper submitted for the CIGRE Session 2020, SC-B1, August 24 – September 3, 2020, online.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ainhirn, F., Woschitz, R., Schichler, U. et al. Extended thermal rating calculations of 400 kV XLPE cables for urban grid applications based on long-term experimental data. Elektrotech. Inftech. (2020). https://doi.org/10.1007/s00502-020-00841-6

Download citation

Keywords

  • power cables
  • thermal rating
  • calculation validation
  • empirical data
  • artificial intelligence